Sleep Disordered Breathing (SDB) has been traditionally identified as being associated with Obstructive Sleep Apnea (OSA) and Cheyne-Stokes Respiration (CSR). Today there are a number of other conditions also recognised as being associated with SDB including, e.g., cardiovascular disease, stroke and diabetes, etc. Patients with these conditions and SDB may benefit from the treatment of their SDB with positive pressure ventilatory support by some form of mechanical ventilator.
While basic nasal Continuous Positive Airway Pressure (CPAP) ventilators may not monitor their patients, in general, the patients benefit from having a device which monitors the patients as part of some kind of control loop. In particular devices are known to monitor pressure, flow and patient effort.
An existing problem for known devices includes discriminating between obstructive sleep apnea (OSA) and central sleep apnea (CSA). OSA is indicative of upper airway collapse and can be used as an input to auto-titration algorithms for the CPAP pressure applied or the end-expiratory pressure (EEP) used in a bi-level device. CSA can be indicative of over-ventilation and can therefore be used as an input to algorithms that auto-titrate the ventilation of the patient. Clearly, miscategorising an apnea as either closed or open results in these titration algorithms prescribing sub-optimal parameters for the treatment of the patient.
Obstructive and central sleep apnea are discriminated in known devices by injecting a 1 cm peak-to-peak 4 Hz oscillation into the treatment pressure waveshape and measuring the resulting 4 Hz flow. The phasic difference in the flow to the pressure waveshape is indicative of the compliance of the load which is then used to deduce if the upper airway is opened or closed. However, this method is uncomfortable for the patient as 4 Hz is easily within the frequency band that can be perceived by the patient. Also, this method does not give any information on events that include upper airway narrowing/closure and simultaneous central sleep apnea.
Obstructive and central sleep apnea are also discriminated in known device by detecting the cardiogenic flow. The cardiogenic flow is the airflow induced in the lungs during a heart beat due to the proximity of the lungs to the heart. During OSA, there is therefore never any cardiogenic flow. Like the previous solution, it is also unable to determine if CSA and OSA have occurred concurrently.
Another existing problem for known devices includes inferring high patient respiratory effort. Patient respiratory effort is a key indicator used by clinicians when evaluating the acute state of a patient in a number of diseases including sleep apnea, obstructive lung disease, and various restrictive diseases. Despite its known value, it has not enjoyed widespread use as either an input to flow generator titration algorithms or as a recorded clinical parameter due to the inconvenience or impracticality of the transducers involved.
The “gold standard” in terms of accuracy for monitoring effort is an oesophageal catheter which a patient is required to swallow. Unfortunately, this is uncomfortable and awkward for a patient and not practical outside a clinic. Respiratory bands around the patient's chest and abdomen are known to monitor effort. Suprasternal notch effort sensors are also known, as well as the use of EMG and ECG sensors. These techniques are all unsuitable for home use.
Another existing problem for known devices includes measuring and storing vaso-specific parameters, such as cardiac afterload, vascular tone, heart rate variability, sympathetic nervous system activity in general, and/or central venous pressure. If these parameters were available in real-time in a flow generator, they could be used to (a) contribute to auto-titration algorithms and (b) be recorded with respiratory specific parameters to allow physicians, to observe long-term trends and have a richer data set to determine the long term management of the patient.
Yet another existing problem for known devices includes limiting the mean mask pressure. Auto-titrating CPAP algorithms aimed at eliminating OSA or upper airway resistance syndrome (UARS) may use breath flow analysis to limit upper airway narrowing. Pressure beyond certain levels may, in some patients, be deleterious to cardiac function. Equally, a lower pressure may be beneficial to cardiac function provided it did not result in complete closure of the upper airway. It is desirable to include cardiovascular parameters in auto-titration schemes such that respiratory therapy (e.g., CPAP pressure) can be continuously optimised. Such parameters may include cardiac afterload, vascular tone, heart rate variability, sympathetic nervous system activity in general, and/or central venous pressure if they could be acquired non-invasively and conveniently.
ResMed's AutoSet CS and AutoSet CS2 devices specifically target patients with heart disease. These devices address the ‘excessive CPAP pressure’ problem by imposing a maximum average pressure of 15 cm H2O.
Another known sensor is a suprasternal notch effort sensor. See U.S. Pat. No. 6,445,942 (Berthon-Jones). Other known techniques for monitoring apneas and hypopneas are described in U.S. Pat. No. 6,091,973 (Colla et al.) and U.S. Pat. No. 6,363,270 (Colla et al.). Another related U.S. patent is U.S. Pat. No. 5,704,345 (Berthon-Jones) which describes distinguishing open and closed airway apneas amongst other things. U.S. Pat. No. 6,484,719 (Berthon-Jones) describes a servo-ventilator which uses a flow sensor. The contents of all these patents are hereby expressly incorporated by cross-reference.